考虑电价引导下的电动汽车充电负荷波动对配电系统电压质量的影响,提出了住宅区电动汽车代理商定价策略制定方法。首先,通过拉丁超立方采样技术构建电动汽车充电场景,根据主从博弈理论确定各充电场景的充电起始时间,建立电动汽车动态概率负荷模型。其次,应用半不变量动态概率潮流求解各节点的电压幅值概率分布,以此评估电压合格情况,并以代理商期望收益最大为目标,以电价波动限值和电压合格率期望值为约束,建立代理商定价策略。再次,采用双层粒子群算法求解电动汽车代理商定价策略,在底层优化中处理电价约束条件,顶层优化中处理系统约束条件。最后,在IEEE 33节点配电系统中进行仿真分析,仿真结果表明:相较无序充电,所提出定价策略优化得到的动态电价能够显著改善不同电动汽车规模下节点电压幅值的动态概率特性,使其满足电压合格率期望值约束,并保证代理商总收益随着电动汽车接入数量增加而稳定增长。 Considering the influence of electric vehicle charging load fluctuation on the voltage quality of power distribution system under the guidance of electricity price, this paper puts forward a method to formulate the pricing strategy of electric vehicle dealers in residential area. Firstly, the scene of electric vehicle charging is constructed through Latin Hypercube Sampling, and the charging starting time of each charging scene is determined according to the master-slave game theory, and the dynamic probability load model of electric vehicle is established. Secondly, the semi-invariant dynamic probability flow is used to solve the voltage amplitude distribution of each node, so as to evaluate the qualified voltage. With the goal of maximizing the expected profit of agents, the limit of electricity price volatility and the expected value of voltage qualified rate are set as constraints Agent pricing strategy. Thirdly, a two-layer particle swarm algorithm is used to solve the pricing strategy of EV dealership, which deals with the constraint of electricity price in the bottom-level optimization and the system constraints in the top-level optimization. Finally, the IEEE 33-bus power distribution system is used to simulate and analyze the results. The simulation results show that compared with the out-of-order charging, the proposed dynamic pricing strategy can significantly improve the dynamic probability of node voltage amplitude under different scale of EVs. Make it meet the expected value of the voltage pass rate constraints, and to ensure that the agents total revenue with the number of electric vehicles increased and stable growth.